package com.zzyl.serve.service.impl;

import java.time.LocalDateTime;
import java.util.List;


import cn.hutool.json.JSON;
import cn.hutool.json.JSONUtil;
import com.baomidou.mybatisplus.core.conditions.query.LambdaQueryWrapper;
import com.zzyl.common.ai.AIModelInvoker;
import com.zzyl.common.core.domain.AjaxResult;
import com.zzyl.common.exception.base.BaseException;
import com.zzyl.common.utils.PDFUtil;
import com.zzyl.common.utils.StringUtils;
import com.zzyl.oss.AliyunOSSOperator;
import com.zzyl.serve.domain.Elder;
import com.zzyl.serve.dto.HealthAssessmentDto;
import com.zzyl.serve.mapper.ElderMapper;
import com.zzyl.serve.util.IDCardUtils;
import com.zzyl.serve.vo.AbnormalDataVo;
import com.zzyl.serve.vo.HealthReportVo;
import org.springframework.beans.BeanUtils;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.data.redis.core.RedisTemplate;
import org.springframework.stereotype.Service;
import com.zzyl.serve.mapper.HealthAssessmentMapper;
import com.zzyl.serve.domain.HealthAssessment;
import com.zzyl.serve.service.IHealthAssessmentService;
import com.baomidou.mybatisplus.extension.service.impl.ServiceImpl;
import org.springframework.web.multipart.MultipartFile;

import java.util.Arrays;

import static com.zzyl.common.constant.RedisKeyConstants.HEALTH_ASSESSMENT_KEY;

/**
 * 健康评估Service业务层处理
 *
 * @author jsz_bamboo
 * @date 2025-05-04
 */
@Service
public class HealthAssessmentServiceImpl extends ServiceImpl<HealthAssessmentMapper, HealthAssessment> implements IHealthAssessmentService {
    @Autowired
    private HealthAssessmentMapper healthAssessmentMapper;

    @Autowired
    private RedisTemplate redisTemplate;

    @Autowired
    private AliyunOSSOperator aliyunOSSOperator;

    @Autowired
    private AIModelInvoker aiModelInvoker;
    @Autowired
    private ElderMapper elderMapper;


    /**
     * 查询健康评估
     *
     * @param id 健康评估主键
     * @return 健康评估
     */
    @Override
    public HealthAssessment selectHealthAssessmentById(Long id) {
        return getById(id);
    }

    /**
     * 查询健康评估列表
     *
     * @param healthAssessment 健康评估
     * @return 健康评估
     */
    @Override
    public List<HealthAssessment> selectHealthAssessmentList(HealthAssessment healthAssessment) {
        return healthAssessmentMapper.selectHealthAssessmentList(healthAssessment);
    }

    /**
     * 新增健康评估
     *
     * @param healthAssessmentDto 健康评估
     * @return 结果
     */
    @Override
    public int insertHealthAssessment(HealthAssessmentDto healthAssessmentDto) {

        //1. 设计prompt：（结合Redis中的内容 + 模板 得到prompt）

        //1.1调用aiModelInvoker中qianfanInvoker()方法,将提示词作为参数传递,接受ai所输出的内容.
        //编写提示词
        //prompt:提示词资料中提供好的
        //只需要将pdf的文本内容拼接到提示词中
        //从redis数据库中获取pdf的文本(通过key)
        String key = HEALTH_ASSESSMENT_KEY + healthAssessmentDto.getIdCard();
        String text = (String) redisTemplate.opsForValue().get(key);

        if (StringUtils.isEmpty(text)) {
            throw new BaseException("没有上传检测报告,请先上传检测报告!!");
        }

        String prompt = "请以一个专业医生的视角来分析这份体检报告，报告中包含了一些异常数据，我需要您对这些数据进行解读，并给出相应的健康建议。\n" +
                "体检内容如下：\n" +
                text +
                "\n" +
                "要求：\n" +
                "1. 提取体检报告中的“总检日期”；\n" +
                "2. 通过临床医学、疾病风险评估模型和数据智能分析，给该用户的风险等级和健康指数给出结果。风险等级分为：健康、提示、风险、危险、严重危险.健康指数范围为0至100分；\n" +
                "3. 根据用户身体各项指标数据，详细说明该用户各项风险等级的占比是多少，最多保留两位小数。结论格式：该用户健康占比20.00%，提示占比20.00%，风险占比20%，危险占比20%，严重危险占比20%；\n" +
                "4. 对于体检报告中的异常数据，请列出（异常数据的结论、体检项目名称、检查结果、参考值、单位、异常解读、建议）这8字段。解读异常数据，解决这些数据可能代表的健康问题或风险。分析可能的原因，包括但不限于生活习惯、饮食习惯、遗传因素等。基于这些异常数据和可能的原因，请给出具体的健康建议，包括饮食调整、运动建议、生活方式改变以及是否需要进一步检查或治疗等。\n" +
                "结论格式：异常数据的结论：肥胖，体检项目名称：体重指数BMI，检查结果：29.2，参考值>24，单位：-。异常解读：体重超标包括超重与肥胖。体重指数（BMI）=体重（kg）/身⾼（m）的平⽅，BMI≥24为超重，BMI≥28为肥胖；男性腰围≥90cm和⼥性腰围≥85cm为腹型肥胖。体重超标是⼀种由多因素（如遗传、进⻝油脂较多、运动少、疾病等）引起的慢性代谢性疾病，尤其是肥胖，已经被世界卫⽣组织列为导致疾病负担的⼗⼤危险因素之⼀。AI建议：采取综合措施预防和控制体重，积极改变⽣活⽅式，宜低脂、低糖、⾼纤维素膳⻝，多⻝果蔬及菌藻类⻝物，增加有氧运动。若有相关疾病（如⾎脂异常、⾼⾎压、糖尿病等）应积极治疗。\n" +
                "5. 根据这个体检报告的内容，分别给人体的8大系统打分，每项满分为100分，8大系统分别为：呼吸系统、消化系统、内分泌系统、免疫系统、循环系统、泌尿系统、运动系统、感官系统\n" +
                "6. 给体检报告做一个总结，总结格式：体检报告中尿蛋⽩、癌胚抗原、⾎沉、空腹⾎糖、总胆固醇、⽢油三酯、低密度脂蛋⽩胆固醇、⾎清载脂蛋⽩B、动脉硬化指数、⽩细胞、平均红细胞体积、平均⾎红蛋⽩共12项指标提示异常，尿液常规共1项指标处于临界值，⾎脂、⾎液常规、尿液常规、糖类抗原、⾎清酶类等共43项指标提示正常，综合这些临床指标和数据分析：肾脏、肝胆、⼼脑⾎管存在隐患，其中⼼脑⾎管有“⾼危”⻛险；肾脏部位有“中危”⻛险；肝胆部位有“低危”⻛险。\n" +
                "\n" +
                "输出要求：\n" +
                "最后,将以上结果输出为JSON格式，其中风险等级使用中文显示,不要包含其他的文字说明，所有的返回结果都是json，详细格式如下：\n" +
                "\n" +
                "{\n" +
                "  \"totalCheckDate\": \"YYYY-MM-DD\",\n" +
                "  \"healthAssessment\": {\n" +
                "    \"riskLevel\": \"healthy/caution/risk/danger/severeDanger\",\n" +
                "    \"healthIndex\": XX.XX\n" +
                "  },\n" +
                "  \"riskDistribution\": {\n" +
                "    \"healthy\": XX.XX,\n" +
                "    \"caution\": XX.XX,\n" +
                "    \"risk\": XX.XX,\n" +
                "    \"danger\": XX.XX,\n" +
                "    \"severeDanger\": XX.XX\n" +
                "  },\n" +
                "  \"abnormalData\": [\n" +
                "    {\n" +
                "      \"conclusion\": \"异常数据的结论\",\n" +
                "      \"examinationItem\": \"体检项目名称\",\n" +
                "      \"result\": \"检查结果\",\n" +
                "      \"referenceValue\": \"参考值\",\n" +
                "      \"unit\": \"单位\",\n" +
                "      \"interpret\":\"对于异常的结论进一步详细的说明\",\n" +
                "      \"advice\":\"针对于这一项的异常，给出一些健康的建议\"\n" +
                "    }\n" +
                "  ],\n" +
                "  \"systemScore\": {\n" +
                "    \"breathingSystem\": XX,\n" +
                "    \"digestiveSystem\": XX,\n" +
                "    \"endocrineSystem\": XX,\n" +
                "    \"immuneSystem\": XX,\n" +
                "    \"circulatorySystem\": XX,\n" +
                "    \"urinarySystem\": XX,\n" +
                "    \"motionSystem\": XX,\n" +
                "    \"senseSystem\": XX\n" +
                "  },\n" +
                "  \"summarize\": \"体检报告的总结\"\n" +
                "}";

        //2. 调用千帆大模型进行请求
        //因为我们提示词的要求返回的是json格式的数据.
        String result = aiModelInvoker.qianfanInvoker(prompt);

        //3. 解析返回的json数据，使用vo接收
        //JSONUtil.toBean(json格式的字符串,需要转化成的实体类)
        HealthReportVo healthReportVo = JSONUtil.toBean(result, HealthReportVo.class);

        //4. 封装数据需要 HealthAssessment 对象属性(我们需要往数据库中插入数据)
        HealthAssessment healthAssessment = new HealthAssessment();
        //属性拷贝
        BeanUtils.copyProperties(healthAssessmentDto, healthAssessment);

        // 封装 身份证号、age、性别、 出生日期
        //age、性别、出生日期是通过身份证解析出来的(调用身份证解析的工具类)
        healthAssessment.setBirthDate(IDCardUtils.getBirthDateByIdCard(healthAssessmentDto.getIdCard()));
        healthAssessment.setAge(IDCardUtils.getAgeByIdCard(healthAssessmentDto.getIdCard()));
        healthAssessment.setGender(IDCardUtils.getGenderFromIdCard(healthAssessmentDto.getIdCard()));

        // 通过ai返回的数据，进行封装
        // 封装：日期、 健康评分、危险等级、 评估时间、报告总结、疾病风险、异常分析、健康系统分值
        healthAssessment.setTotalCheckDate(healthReportVo.getTotalCheckDate());
        healthAssessment.setHealthScore(String.valueOf(healthReportVo.getHealthAssessment().getHealthIndex()));
        healthAssessment.setRiskLevel(healthReportVo.getHealthAssessment().getRiskLevel());
        healthAssessment.setAssessmentTime(LocalDateTime.now());//当前的时间
        healthAssessment.setReportSummary(healthReportVo.getSummarize());
        healthAssessment.setDiseaseRisk(JSONUtil.toJsonStr(healthReportVo.getRiskDistribution()));
        healthAssessment.setAbnormalAnalysis(JSONUtil.toJsonStr(healthReportVo.getAbnormalData()));
        healthAssessment.setSystemScore(JSONUtil.toJsonStr(healthReportVo.getSystemScore()));

        // 入住建议、护理等级、入住情况
        // 判断健康分数，如果低于60分不建议入住
        if (healthAssessment.getHealthScore().compareTo("60") < 0) {
                healthAssessment.setSuggestionForAdmission(1);
        }else {
            healthAssessment.setSuggestionForAdmission(0);
        }

        //如果入住需要根据健康分数来选择何种护理等级
        String nursingLevelName = getNursingLevelName(Double.valueOf(healthAssessment.getHealthScore()));
        healthAssessment.setNursingLevelName(nursingLevelName);

        //入住情况查询数据库
        Elder elder = elderMapper.selectOne(
                new LambdaQueryWrapper<Elder>()
                        .eq(Elder::getIdCardNo, healthAssessment.getIdCard())
                        .eq(Elder::getStatus, 1)
        );

        if (elder!=null){
            healthAssessment.setAdmissionStatus(0);
        }else {
            healthAssessment.setAdmissionStatus(1);
        }



        //5. 调用mapper进行插入
        this.save(healthAssessment);

        //6. 数据库体检评测保存成功后，可以删除Redis缓存的体检信息：
            redisTemplate.delete(key);

        //7. 返回id进行响应

        return healthAssessment.getId();
    }
    /**
     * 根据分数获取护理等级
     * @param healthScore
     * @return
     */
    private String getNursingLevelName(double healthScore) {
        if(healthScore<0 || healthScore>100){
            throw new BaseException("健康评分不在0-100之间");
        }
        if (healthScore>=90) {
            return "三级护理";
        }else if (healthScore>=80){
            return "二级护理";
        }else if (healthScore>=70){
            return "一级护理";
        }else if(healthScore>=60){
            return "特级护理";
        }
        return "不建议入住";
    }
    /**
     * 修改健康评估
     *
     * @param healthAssessment 健康评估
     * @return 结果
     */
    @Override
    public int updateHealthAssessment(HealthAssessment healthAssessment) {
        return updateById(healthAssessment) ? 1 : 0;
    }

    /**
     * 批量删除健康评估
     *
     * @param ids 需要删除的健康评估主键
     * @return 结果
     */
    @Override
    public int deleteHealthAssessmentByIds(Long[] ids) {
        return removeByIds(Arrays.asList(ids)) ? 1 : 0;
    }

    /**
     * 删除健康评估信息
     *
     * @param id 健康评估主键
     * @return 结果
     */
    @Override
    public int deleteHealthAssessmentById(Long id) {
        return removeById(id) ? 1 : 0;
    }

    /**
     * 上传文件
     *
     * @param idCardNo
     * @param file
     * @return
     */
    @Override
    public AjaxResult upload(String idCardNo, MultipartFile file) {

        try {
            //1.上传到OSS
            String url = aliyunOSSOperator.upload(file.getBytes(), file.getOriginalFilename());

            //2.将PDF转化成文本
            String text = PDFUtil.pdfToString(file.getInputStream());

            //3.将文本存入到redis中 key:idCardNo,  value: text
            String key = HEALTH_ASSESSMENT_KEY + idCardNo;
            redisTemplate.opsForValue().set(key, text);

            //4.封装返回结果
            AjaxResult ajaxResult = AjaxResult.success();


            ajaxResult.put("fileName", url);
            ajaxResult.put("url", url);
            ajaxResult.put("originalFilename", file.getOriginalFilename());

            return ajaxResult;

        } catch (Exception e) {
            throw new RuntimeException(e);
        }

    }
}
